AI for agritech in India

Agritech platforms in India talk to farmers in a dozen languages, over patchy connectivity, about advice that needs to be both simple and correct. unoblox gives agritech teams one rupee-billed, OpenAI-compatible endpoint for GPT, Claude, DeepSeek, Qwen, Llama and more, so a farmer-facing product can be built and billed entirely in India without a foreign card or a separate translation vendor.

What agritech teams actually build with it

The common patterns are drafting, not deciding: turning an agronomist-approved advisory into a farmer-readable message, summarising mandi price notes or scheme circulars that are already available as text, answering common crop questions with a draft that an agronomist reviews before it goes out, and translating advisory content into a farmer's preferred language. None of this substitutes for expert agronomic judgement — it speeds up producing the first draft.

Real multilingual models, not an invented "farm language" model

India's agricultural workforce spans Hindi, Marathi, Punjabi, Tamil, Telugu, Kannada and more, and it's tempting to look for a model built specifically for this. unoblox does not offer a bespoke agri-language model, and no such model exists in the catalogue — instead, use a model with broad multilingual training, such as qwen/qwen3-235b-a22b-instruct-2507, meta-llama/llama-4-scout-17b-16e-instruct, or openai/gpt-5, and have a native speaker check tone and agricultural terminology before content reaches farmers.

Picking a model for very high query volumes

• Free pilots: qwen/qwen3-1.7b costs nothing to call, useful for testing a query-answering flow before it carries real traffic.
• High-volume production drafting: deepseek-ai/deepseek-v4-flash at ₹9.07 / ₹18.14 per 1M input/output tokens keeps per-query cost low at scale.
• Faster multilingual drafting: meta-llama/llama-4-scout-17b-16e-instruct at ₹10.08 / ₹30.24.
• More complex summarisation: qwen/qwen3-235b-a22b-instruct-2507 at ₹9.07 / ₹55.44, useful for longer advisory or scheme documents.

Live pricing for every model, including the rest of the catalogue, is always on /models.

Wiring it into an existing farmer channel

curl https://api.unoblox.ai/v1/chat/completions \
  -H "Authorization: Bearer ub-gw-xxxxxxxxxxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-ai/deepseek-v4-flash",
    "messages": [{"role": "user", "content": "Rewrite this advisory in simple Hindi for a farmer audience."}]
  }'

unoblox is the inference layer; your team still owns the SMS gateway, WhatsApp Business integration or IVR system that actually reaches the farmer.

Frequently asked questions

Is there a model built specifically for Indian regional or agricultural language? No, and unoblox won't claim otherwise. Use a general multilingual model from the catalogue and review its output for local terminology before publishing.

Can farmers trust the advisory text without an agronomist reviewing it first? It should be reviewed. These models draft and summarise; they don't verify agronomic facts, so a human expert should sign off before advice reaches a farmer.

Does unoblox provide the WhatsApp or SMS layer to reach farmers? No. unoblox is the OpenAI-compatible inference API; you connect it to whatever messaging channel your platform already uses.

Is farmer data processed in India? Only for the free, unoblox-hosted qwen/qwen3-1.7b model. Larger models run on their original providers' infrastructure outside India.

Is there a genuinely free way to start? Yes, qwen/qwen3-1.7b is ₹0 per token, enough to build and test a first version.

How is this billed as our farmer base grows? Per token actually used, in rupees, on one monthly GST invoice — cost scales with usage, not with a fixed per-seat fee.

Get started in rupees → https://unoblox.ai/sign-in